Prediction Model And Application Of Enterprise Carbon Credit Risk

In recent years, the concern about environmental issues continued to rise. Since two sessions "O ne proposal" locked in low-carbon economy in 2010, China has continued to explore the practice of development of low-carbon economic development and environmental sustainability. However, that several years of practice has proved that relying solely on enforcement tools bundles or purely administrative power, unable to continue our path of sustainable development. Learn from the successful experience of foreign countries in the development of low-carbon economy, we need to establish a low carbon financial support of low carbon eco nomy management system urgently. Considering the Bank of C hina’s dominant position in the financial sector, if it takes the positive ways to development carbon credits business, it will be undoubtedly one of the effective ways.On the basis of the theories of social responsibility theory, the theory of sustainable development and international Equator Principles, this paper analyzes the causes of the development of carbon credits of commercial banks. Secondly, from a business point of view, combined with a carbon credit risk characteristics, we established an index system of corporate carbon credit risk prediction. Select the listed companies as samples, and according to some estab lished standard, we assess the credit risk of carbon credit rating of the sample of companies. Furthermore, we used BP neural network to establish a carbon credit risk prediction models respectively, from the time series and cross-sectional dimensions of data dimensions. Through the training and simulation of a network, we analyze the reliability of models and evaluate the performance of the two models. Finally, the forecasting models are applied to real life, we concluded that the time series forecasting model dimension is more valuable in practical.